Triple

T29566408
Position Surface form Disambiguated ID Type / Status
Subject Bowling Green, Ohio E753173 entity
Predicate hasLibrary P35 FINISHED
Object Wood County District Public Library
Wood County District Public Library is a public library system serving residents of Wood County, Ohio, with books, digital resources, and community programs.
E1874099 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Wood County District Public Library | Statement: [Bowling Green, Ohio, hasLibrary, Wood County District Public Library]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wood County District Public Library
Triple: [Bowling Green, Ohio, hasLibrary, Wood County District Public Library]
Generated description
Wood County District Public Library is a public library system serving residents of Wood County, Ohio, with books, digital resources, and community programs.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f0ef7fcb4881908a933110adb9bda1 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66d4323708190a12d588bf6a512b3 completed May 2, 2026, 9:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a262d68eff88190bbdbcb569e590116 completed June 8, 2026, 2:48 a.m.
NEDg Description generation batch_6a26317def3881908eb2e11b7754e1ac completed June 8, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a2635aebca08190bedcd6f2c3e9d58c completed June 8, 2026, 3:23 a.m.
Created at: April 28, 2026, 5:52 p.m.